Статті в журналах з теми "DC (Difference of Convex functions) programming and DCA (DC Algorithms)"
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Le, Hoai Minh, Hoai An Le Thi, Tao Pham Dinh, and Van Ngai Huynh. "Block Clustering Based on Difference of Convex Functions (DC) Programming and DC Algorithms." Neural Computation 25, no. 10 (October 2013): 2776–807. http://dx.doi.org/10.1162/neco_a_00490.
Le Thi, Hoai An, and Vinh Thanh Ho. "Online Learning Based on Online DCA and Application to Online Classification." Neural Computation 32, no. 4 (April 2020): 759–93. http://dx.doi.org/10.1162/neco_a_01266.
Le Thi, Hoai An, Xuan Thanh Vo, and Tao Pham Dinh. "Efficient Nonnegative Matrix Factorization by DC Programming and DCA." Neural Computation 28, no. 6 (June 2016): 1163–216. http://dx.doi.org/10.1162/neco_a_00836.
Kebaili, Zahira, and Mohamed Achache. "Solving nonmonotone affine variational inequalities problem by DC programming and DCA." Asian-European Journal of Mathematics 13, no. 03 (December 17, 2018): 2050067. http://dx.doi.org/10.1142/s1793557120500679.
Phan, Duy Nhat, Hoai An Le Thi, and Tao Pham Dinh. "Sparse Covariance Matrix Estimation by DCA-Based Algorithms." Neural Computation 29, no. 11 (November 2017): 3040–77. http://dx.doi.org/10.1162/neco_a_01012.
Wang, Meihua, Fengmin Xu, and Chengxian Xu. "A Branch-and-Bound Algorithm Embedded with DCA for DC Programming." Mathematical Problems in Engineering 2012 (2012): 1–16. http://dx.doi.org/10.1155/2012/364607.
Li, Jieya, and Liming Yang. "Robust sparse principal component analysis by DC programming algorithm." Journal of Intelligent & Fuzzy Systems 39, no. 3 (October 7, 2020): 3183–93. http://dx.doi.org/10.3233/jifs-191617.
Le Thi, Hoai An, Manh Cuong Nguyen, and Tao Pham Dinh. "A DC Programming Approach for Finding Communities in Networks." Neural Computation 26, no. 12 (December 2014): 2827–54. http://dx.doi.org/10.1162/neco_a_00673.
An, Le Thi Hoai, and Pham Dinh Tao. "The DC (Difference of Convex Functions) Programming and DCA Revisited with DC Models of Real World Nonconvex Optimization Problems." Annals of Operations Research 133, no. 1-4 (January 2005): 23–46. http://dx.doi.org/10.1007/s10479-004-5022-1.
Ji, Ying, and Shaojian Qu. "Proximal Point Algorithms for Vector DC Programming with Applications to Probabilistic Lot Sizing with Service Levels." Discrete Dynamics in Nature and Society 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/5675183.
Yang, Liming, Zhuo Ren, Yidan Wang, and Hongwei Dong. "A Robust Regression Framework with Laplace Kernel-Induced Loss." Neural Computation 29, no. 11 (November 2017): 3014–39. http://dx.doi.org/10.1162/neco_a_01002.
Ling, Jiajing, Tarun Gupta, and Akshat Kumar. "Reinforcement Learning for Zone Based Multiagent Pathfinding under Uncertainty." Proceedings of the International Conference on Automated Planning and Scheduling 30 (June 1, 2020): 551–59. http://dx.doi.org/10.1609/icaps.v30i1.6751.
Xu, Hai-Ming, Hui Xue, Xiao-Hong Chen, and Yun-Yun Wang. "Solving Indefinite Kernel Support Vector Machine with Difference of Convex Functions Programming." Proceedings of the AAAI Conference on Artificial Intelligence 31, no. 1 (February 13, 2017). http://dx.doi.org/10.1609/aaai.v31i1.10889.
Aragón-Artacho, F. J., R. Campoy, and P. T. Vuong. "The Boosted DC Algorithm for Linearly Constrained DC Programming." Set-Valued and Variational Analysis, December 21, 2022. http://dx.doi.org/10.1007/s11228-022-00656-x.
Awasthi, Pranjal, Anqi Mao, Mehryar Mohri, and Yutao Zhong. "DC-programming for neural network optimizations." Journal of Global Optimization, January 2, 2024. http://dx.doi.org/10.1007/s10898-023-01344-2.
Moudafi, Abdellatif. "Difference of two norms-regularizations for Q-Lasso." Applied Computing and Informatics ahead-of-print, ahead-of-print (August 5, 2020). http://dx.doi.org/10.1016/j.aci.2018.07.002.
D’Alessandro, Pietro, Manlio Gaudioso, Giovanni Giallombardo, and Giovanna Miglionico. "The Descent–Ascent Algorithm for DC Programming." INFORMS Journal on Computing, December 14, 2023. http://dx.doi.org/10.1287/ijoc.2023.0142.